use of com.google.cloud.vision.v1p4beta1.OperationMetadata in project java-automl by googleapis.
the class UndeployModel method undeployModel.
// Undeploy a model from prediction
static void undeployModel(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
UndeployModelRequest request = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(request);
future.get();
System.out.println("Model undeployment finished");
}
}
use of com.google.cloud.vision.v1p4beta1.OperationMetadata in project java-automl by googleapis.
the class VisionClassificationCreateModel method createModel.
// Create a model
static void createModel(String projectId, String datasetId, String displayName) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// A resource that represents Google Cloud Platform location.
LocationName projectLocation = LocationName.of(projectId, "us-central1");
// Set model metadata.
ImageClassificationModelMetadata metadata = ImageClassificationModelMetadata.newBuilder().setTrainBudgetMilliNodeHours(24000).build();
Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setImageClassificationModelMetadata(metadata).build();
// Create a model with the model metadata in the region.
OperationFuture<Model, OperationMetadata> future = client.createModelAsync(projectLocation, model);
// OperationFuture.get() will block until the model is created, which may take several hours.
// You can use OperationFuture.getInitialFuture to get a future representing the initial
// response to the request, which contains information while the operation is in progress.
System.out.format("Training operation name: %s\n", future.getInitialFuture().get().getName());
System.out.println("Training started...");
}
}
use of com.google.cloud.vision.v1p4beta1.OperationMetadata in project java-automl by googleapis.
the class ClassificationDeployModelNodeCount method classificationDeployModelNodeCount.
// Deploy a model with a specified node count
static void classificationDeployModelNodeCount(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
// Set how many nodes the model is deployed on
ImageClassificationModelDeploymentMetadata deploymentMetadata = ImageClassificationModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageClassificationModelDeploymentMetadata(deploymentMetadata).build();
// Deploy the model
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
future.get();
System.out.println("Model deployment on 2 nodes finished");
}
}
use of com.google.cloud.vision.v1p4beta1.OperationMetadata in project java-automl by googleapis.
the class VisionObjectDetectionDeployModelNodeCount method visionObjectDetectionDeployModelNodeCount.
// Deploy a model for prediction with a specified node count (can be used to redeploy a model)
static void visionObjectDetectionDeployModelNodeCount(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
ImageObjectDetectionModelDeploymentMetadata metadata = ImageObjectDetectionModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageObjectDetectionModelDeploymentMetadata(metadata).build();
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
future.get();
System.out.println("Model deployment finished");
}
}
use of com.google.cloud.vision.v1p4beta1.OperationMetadata in project java-automl by googleapis.
the class ClassificationUndeployModel method classificationUndeployModel.
// Deploy a model
static void classificationUndeployModel(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
// Build deploy model request.
UndeployModelRequest undeployModelRequest = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
// Deploy a model with the deploy model request.
OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(undeployModelRequest);
future.get();
// Display the deployment details of model.
System.out.println("Model undeploy finished");
}
}
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